Keele Research Repository

Background: Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be
fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so
that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic
range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However,
we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these
previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on
the basis of which more of the biology underlying ACI success or failure can be understood.
Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from
ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at
the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and
combined iTRAQ and LF datasets were investigated using pathway and network analyses.
Results: iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to
cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders
and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between
responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The
differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed
biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that
was used to generate interactome networks representing ACI success or failure. Functional pathways that are
dysregulated in ACI non-responders were identified, including acute-phase response signalling.
Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of
the SF proteome in responders and non-responders to ACI has been profiled, providing a better understanding of the
biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in nonresponders.
Keywords: Autologous chondrocyte implantation (ACI), iTRAQ proteomics, Label-free quantitation proteomics, Synovial
fluid, Cartilage repair, Complement C1S subcomponent, Matrix metalloproteinase 3, MMP3